Text Classification
Transformers
ONNX
Safetensors
English
distilbert
intent-classification
multitask
iab
conversational-ai
adtech
calibrated-confidence
text-embeddings-inference
Instructions to use admesh/agentic-intent-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use admesh/agentic-intent-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="admesh/agentic-intent-classifier")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("admesh/agentic-intent-classifier", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload iab_classifier.py with huggingface_hub
Browse files- iab_classifier.py +8 -3
iab_classifier.py
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@@ -4,9 +4,14 @@ from functools import lru_cache
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import torch
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def round_score(value: float) -> float:
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import torch
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try:
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from .config import IAB_PARENT_FALLBACK_CONFIDENCE_FLOOR # type: ignore
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from .iab_taxonomy import get_iab_taxonomy, parse_path_label, path_to_label # type: ignore
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from .model_runtime import get_head # type: ignore
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except ImportError:
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from config import IAB_PARENT_FALLBACK_CONFIDENCE_FLOOR
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from iab_taxonomy import get_iab_taxonomy, parse_path_label, path_to_label
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from model_runtime import get_head
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def round_score(value: float) -> float:
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